Lecture topics: - Fundamentals of Music Theory I - notes, markings, tuning - Fundamentals of Music Theory II - harmony, instruments, musical styles - Repeating the basics of digital signal processing with a view to its use in audio processing - Discrete Fourier transform, short-term Fourier transform, signal spectrum, LTI systems and Z-transforms, filters and their basic types and properties, filter structures, filter design methods - Digital audio effects I - EQ, reverb, echo - Digital audio effects II - vibrato, tremolo, chorus, flanger, wah-wah, phaser - Digital audio effects III - dynamic compression and expansion, noise gate, multiband dynamic compression, side-compression - Digital Audio Effects VI - non-linear effects, vocoder, pitch-shifter, time-stretching - Single-channel speech enhancement methods - Wiener filter, binary mask, advanced methods based on DNN training - Acoustic event detection - classical detection methods, DNN training based methods - Acoustic echo cancellation - principles and methods - Reconstruction of corrupted signals, declipping, dereverberation - MP3 format, compression and decompression, psychoacoustic rules Exercises: - Work with music software (Audacity, Cubase), import and export of data for work with Matlab - Programming VST plugins and real-time audio processing - Implementation of noise reduction methods, SNR and SDR evaluation - Data collection and training of simple DNN for event detection - Rhythm and style detection - Acoustic echo cancellation in the frequency domain - Reconstruction of corrupted recordings - Examples to verify psychoacoustic rules, working with mp3 format - Measurement of acoustic impulse response - Estimating the direction of arrival of an acoustic signal
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